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Media Contacts
![This photo is of three men sitting around a laptop computer that happens to be working on cybersecurity testing equipment.](/sites/default/files/styles/list_page_thumbnail/public/2024-07/Picture11.jpg?h=cc1017b3&itok=hCUDThD9)
A newly established internship between ORNL and Maryville College is bringing cybersecurity careers to a local liberal arts college. The internship was established by a Maryville College alumni who recently joined ORNL.
![Arial view of the Atchafalaya Basin](/sites/default/files/styles/list_page_thumbnail/public/2024-07/CoastalEco_atchafalayadelta_pho_2010113.jpg?h=34e43602&itok=_bt6Z5Va)
In the wet, muddy places where America’s rivers and lands meet the sea, scientists from the Department of Energy’s Oak Ridge National Laboratory are unearthing clues to better understand how these vital landscapes are evolving under climate change.
![Man in blue suit and blue and white button down with brown air and brown facial hair smiles for a photo with a green and teal background. Plus a quote](/sites/default/files/styles/list_page_thumbnail/public/2024-07/Picture7.png?h=f23f0227&itok=QhphdCXk)
As a data scientist, Daniel Adams uses storytelling to parse through a large amount of information to determine which elements are most important, paring down the data to result in the most efficient and accurate data set possible.
![Redish orange sample of material, round in size and small (taking up only a quarter of the image). There is a dark grey floor and blue light background](/sites/default/files/styles/list_page_thumbnail/public/2024-06/Picture1.jpg?h=a367a0f1&itok=atewqjdE)
Despite strong regulations and robust international safeguards, authorities routinely interdict nuclear materials outside of regulatory control. Researchers at ORNL are exploring a new method that would give authorities the ability to analyze intercepted nuclear material and determine where it originated.
![Man in blue shirt and grey pants holds laptop and poses next to a green plant in a lab.](/sites/default/files/styles/list_page_thumbnail/public/2024-06/2024-P09065.jpg?h=036a71b7&itok=szEF_SdO)
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
![Caption: Participants gather for a group photo after discussing securing AI systems for critical national security data and applications. Photo by Liz Neunsinger/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-05/Picture1.jpg?h=1758acef&itok=hu9V4GaE)
Researchers at the Department of Energy’s Oak Ridge National Laboratory met recently at an AI Summit to better understand threats surrounding artificial intelligence. The event was part of ORNL’s mission to shape the future of safe and secure AI systems charged with our nation’s most precious data.
![Frontier supercomputer sets new standard in molecular simulation](/sites/default/files/styles/list_page_thumbnail/public/2024-05/OLCF_LammpsBanner.png?h=ae114f5c&itok=h_Bam9gm)
When scientists pushed the world’s fastest supercomputer to its limits, they found those limits stretched beyond even their biggest expectations. In the latest milestone, a team of engineers and scientists used Frontier to simulate a system of nearly half a trillion atoms — the largest system ever modeled and more than 400 times the size of the closest competition.
![Mohamad Zineddin](/sites/default/files/styles/list_page_thumbnail/public/2024-05/Dr%20Z.png?h=2a35d14f&itok=2ZMLdTMr)
Mohamad Zineddin hopes to establish an interdisciplinary center of excellence for nuclear security at ORNL, combining critical infrastructure assessment and protection, risk mitigation, leadership in nuclear security, education and training, nuclear security culture and resilience strategies and techniques.
![Joon-Seok Kim Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-05/joon-seok.jpg?h=d9b3a08b&itok=qiPgBrWQ)
Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people. By simulating an event, such as extreme weather, researchers can see how people might respond to adverse situations, and those outcomes can be used to improve emergency planning.
![Quietly making noise: Measuring differential privacy could balance meaningful analytics and identity protection](/sites/default/files/styles/list_page_thumbnail/public/2024-04/AdobeStock_599537692.jpeg?h=8059516b&itok=oDcA1WvL)
To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.